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Artificial Intelligence for Staging Glaucoma Severity: A Comparison With an Eye Specialist Using Visual Field Tests
Sponsor: University of Salerno
Summary
The study titled "Reliability of Artificial Intelligence in Glaucoma Severity Staging Using the Brusini GSS2 System: A Longitudinal Comparative Study against Expert Assessment" aims to evaluate the diagnostic reliability and clinical utility of an Artificial Intelligence (AI) system in staging glaucoma severity using the Brusini Glaucoma Staging System 2 (GSS2) compared to expert ophthalmologist assessment. The study protocol involves the longitudinal analysis of visual fields (VFs) collected at baseline (T0) and at a 1-year follow-up (T1). Statistical methodology will utilize quadratic weighted Cohen's kappa to assess diagnostic agreement between the AI system and expert assessment, Wilcoxon signed-rank tests to evaluate potential systematic bias, and Spearman's rank correlation to investigate the relationship between longitudinal progression and changes in the clinical Visual Field Index.
Official title: Reliability of Artificial Intelligence in Glaucoma Severity Staging Using the Brusini GSS2 System: A Longitudinal Comparative Study Against Expert Assessment
Key Details
Gender
All
Age Range
Any - Any
Study Type
OBSERVATIONAL
Enrollment
50
Start Date
2011-04-15
Completion Date
2025-07-24
Last Updated
2026-09-15
Healthy Volunteers
Not specified
Conditions
Interventions
Artificial Intelligence GSS2 Staging
An artificial intelligence system used to automatically stage glaucoma severity from standard automated visual field tests according to the Brusini Glaucoma Staging System 2 (GSS2). AI classifications were compared with those of an expert ophthalmologist at baseline and 1-year follow-up. The AI was used for assessment only and did not influence patient management or treatment.
Locations (1)
University of Salerno
Salerno, Italy